Federal Court Invalidates NYC Law Requiring Food Delivery Apps to Share Customer Data with Restaurants

Curated on Posted on by Stefaan Verhulst

Article by Hunton, Andrews, Kurth: “On September 24, 2024, a federal district court held that New York City’s “Customer Data Law” violates the First Amendment. Passed in the summer of 2021, the law requires food-delivery apps to share customer-specific data with restaurants that prepare delivered meals.

The New York City Council enacted the Customer Data Law to boost the local restaurant industry in the wake of the pandemic. The law requires food-delivery apps to provide restaurants (upon the restaurants’ request) with each diner’s full name, email address, phone number, delivery address, and order contents. Customers may opt out of such sharing. The law’s supporters argue that requiring such disclosure addresses exploitation by the delivery apps and helps restaurants advertise more effectively.

Normally, when a customer places an order through a food-delivery app, the app provides the restaurant with the customer’s first name, last initial and food order. Food-delivery apps share aggregate data analytics with restaurants but generally do not share customer-specific data beyond the information necessary to fulfill an order. Some apps, for example, provide restaurants with data related to their menu performance, customer feedback and daily operations.

Major food-delivery app companies challenged the Customer Data Law, arguing that its data sharing requirement compels speech impermissibly under the First Amendment. Siding with the apps, the U.S. District Court for the Southern District of New York declared the city’s law invalid, holding that its data sharing requirement is not appropriately tailored to a substantial government interest…(More)”.

Climate and health data website launched

Curated on Posted on by Stefaan Verhulst

Article by Susan Cosier: “A new website of data resources, tools, and training materials that can aid researchers in studying the consequences of climate change on the health of communities nationwide is now available. At the end of July, NIEHS launched the Climate and Health Outcomes Research Data Systems (CHORDS) website, which includes a catalog of environmental and health outcomes data from various government and nongovernmental agencies.

The website provides a few resources of interest, including a catalog of data resources to aid researchers in finding relevant data for their specific research projects; an online training toolkit that provides tutorials and walk-throughs of downloading, integrating, and visualizing health and environmental data; a listing of publications of note on wildfire and health research; and links to existing resources, such as the NIEHS climate change and health glossary and literature portal.

The catalog includes a listing of dozens of data resources provided by different federal and state environmental and health sources. Users can sort the listing based on environmental and health measures of interest — such as specific air pollutants or chemicals — from data providers including NASA and the U.S. Environmental Protection Agency with many more to come…(More)”.

Rethinking ‘Checks and Balances’ for the A.I. Age

Curated on Posted on by Stefaan Verhulst

Article by Steve Lohr: “A new project, orchestrated by Stanford University and published on Tuesday, is inspired by the Federalist Papers and contends that today is a broadly similar historical moment of economic and political upheaval that calls for a rethinking of society’s institutional arrangements.

In an introduction to its collection of 12 essays, called the Digitalist Papers, the editors overseeing the project, including Erik Brynjolfsson, director of the Stanford Digital Economy Lab, and Condoleezza Rice, secretary of state in the George W. Bush administration and director of the Hoover Institution, identify their overarching concern.

“A powerful new technology, artificial intelligence,” they write, “explodes onto the scene and threatens to transform, for better or worse, all legacy social institutions.”

The most common theme in the diverse collection of essays: Citizens need to be more involved in determining how to regulate and incorporate A.I. into their lives. “To build A.I. for the people, with the people,” as one essay summed it up.

The project is being published as the technology is racing ahead. A.I. enthusiasts see a future of higher economic growth, increased prosperity and a faster pace of scientific discovery. But the technology is also raising fears of a dystopian alternative — A.I. chatbots and automated software not only replacing millions of workers, but also generating limitless misinformation and worsening political polarization. How to govern and guide A.I. in the public interest remains an open question…(More)”.

Need for Co-creating Urban Data Collaborative

Curated on Posted on by Stefaan Verhulst

Blog by Gaurav Godhwani: “…The Government of India has initiated various urban reforms for our cities like — Atal Mission for Rejuvenation and Urban Transformation 2.0 (AMRUT 2.0), Smart Cities Mission (SCM), Swachh Bharat Mission 2.0 (SBM-Urban 2.0) and development of Urban & Industrial Corridors. To help empower cities with data, the Ministry of Housing & Urban Affairs(MoHUA) has also launched various data initiatives including — DataSmart Cities Strategy, Data Maturity Assessment Framework, Smart Cities Open Data Portal, City Innovation Exchange, India Urban Data Exchange and the India Urban Observatory.

Unfortunately, most of the urban data remains in silos and capacities for our cities to harness urban data to improve decision-making, strengthen citizen participation continues to be limited. As per the last Data Maturity Assessment Framework (DMAF) assessment conducted in November 2020 by MoHUA, among 100 smart cities only 45 cities have drafted/ approved their City Data Policies with just 32 cities having a dedicated data budget in 2020–21 for data-related activities. Moreover, in-terms of fostering data collaborations, only 12 cities formed data alliances to achieve tangible outcomes. We hope smart cities continue this practice by conducting a yearly self-assessment to progress in their journey to harness data for improving their urban planning.

Seeding Urban Data Collaborative to advance City-level Data Engagements

There is a need to bring together a diverse set of stakeholders including governments, civil societies, academia, businesses and startups, volunteer groups and more to share and exchange urban data in a secure, standardised and interoperable manner, deriving more value from re-using data for participatory urban development. Along with improving data sharing among these stakeholders, it is necessary to regularly convene, ideate and conduct capacity building sessions and institutionalise data practices.

Urban Data Collaborative can bring together such diverse stakeholders who could address some of these perennial challenges in the ecosystem while spurring innovation…(More)”

Improving Governance Outcomes Through AI Documentation: Bridging Theory and Practice 

Curated on Posted on by Stefaan Verhulst

Report by Amy Winecoff, and Miranda Bogen: “AI documentation is a foundational tool for governing AI systems, via both stakeholders within and outside AI organizations. It offers a range of stakeholders insight into how AI systems are developed, how they function, and what risks they may pose. For example, it might help internal model development, governance, compliance, and quality assurance teams communicate about and manage risk throughout the development and deployment lifecycle. Documentation can also help external technology developers determine what testing they should perform on models they incorporate into their products, or it could guide users on whether or not to adopt a technology. While documentation is essential for effective AI governance, its success depends on how well organizations tailor their documentation approaches to meet the diverse needs of stakeholders, including technical teams, policymakers, users, and other downstream consumers of the documentation.

This report synthesizes findings from an in-depth analysis of academic and gray literature on documentation, encompassing 37 proposed methods for documenting AI data, models, systems, and processes, along with 21 empirical studies evaluating the impact and challenges of implementing documentation. Through this synthesis, we identify key theoretical mechanisms through which AI documentation can enhance governance outcomes. These mechanisms include informing stakeholders about the intended use, limitations, and risks of AI systems; facilitating cross-functional collaboration by bridging different teams; prompting ethical reflection among developers; and reinforcing best practices in development and governance. However, empirical evidence offers mixed support for these mechanisms, indicating that documentation practices can be more effectively designed to achieve these goals…(More)”.

China’s Hinterland Becomes A Critical Datascape

Curated on Posted on by Stefaan Verhulst

Article by Gary Zhexi Zhang: “In 2014, the southwestern province of Guizhou, a historically poor and mountainous area, beat out rival regions to become China’s first “Big Data Comprehensive Pilot Zone,” as part of a national directive to develop the region — which is otherwise best known as an exporter of tobacco, spirits and coal — into the infrastructural backbone of the country’s data industry. Since then, vast investment has poured into the province. Thousands of miles of highway and high-speed rail tunnel through the mountains. Driving through the province can feel vertiginous: Of the hundred highest bridges in the world, almost half are in Guizhou, and almost all were built in the last 15 years.

In 2015, Xi Jinping visited Gui’an New Area to inaugurate the province’s transformation into China’s “Big Data Valley,” exemplifying the central government’s goal to establish “high quality social and economic development,” ubiquitously advertised through socialist-style slogans plastered on highways and city streets…(More)”.

Why Is There Data?

Curated on Posted on by Stefaan Verhulst

Paper by David Sisson and Ilan Ben-Meir: “In order for data to become truly valuable (and truly useful), that data must first be processed. The question animating this essay is thus a straightforward one: What sort of processing must data undergo, in order to become valuable? While the question may be obvious, its answers are anything but; indeed, reaching them will require us to pose, answer – and then revise our answers to – several other questions that will prove trickier than they first appear: Why is data valuable – what is it for? What is “data”? And what does “working with data” actually involve?…(More)”

AI in Global Development Playbook

Curated on Posted on by Stefaan Verhulst

USAID Playbook: “…When used effectively and responsibly, AI holds the potential to accelerate progress on sustainable development and close digital divides, but it also poses risks that could further impede progress toward these goals. With the right enabling environment and ecosystem of actors, AI can enhance efficiency and accelerate development outcomes in sectors such as health, education, agriculture, energy, manufacturing, and delivering public services. The United States aims to ensure that the benefits of AI are shared equitably across the globe.

Distilled from consultations with hundreds of government officials, non-governmental organizations, technology firms and startups, and individuals from around the world, the AI in Global Development Playbook is a roadmap to develop the capacity, ecosystems, frameworks, partnerships, applications, and institutions to leverage safe, secure, and trustworthy AI for sustainable development.

The United States’ current efforts are grounded in the belief that AI, when developed and deployed responsibly, can be a powerful force for achieving the Sustainable Development Goals and addressing some of the world’s most urgent challenges. Looking ahead, the United States will continue to support low- and middle-income countries through funding, advocacy, and convening efforts–collectively navigating the complexities of the digital age and working toward a future in which the benefits of technological development are widely shared.

This Playbook seeks to underscore AI as a uniquely global opportunity with far-reaching impacts and potential risks. It highlights that safe, secure, and trustworthy design, deployment, and use of AI is not only possible but essential. Recognizing that international cooperation and multi-stakeholder partnerships are key in achieving progress, we invite others to contribute their expertise, resources, and perspectives to enrich and expand this framework.

The true measure of progress in responsible AI is not in the sophistication of our machines but in the quality of life the technology enhances. Together we can work toward ensuring the promise of AI is realized in service of this goal…(More)”

Artificial intelligence (AI) in action: A preliminary review of AI use for democracy support

Curated on Posted on by Stefaan Verhulst

Policy paper by Grahm Tuohy-Gaydos: “…provides a working definition of AI for Westminster Foundation for Democracy (WFD) and the broader democracy support sector. It then provides a preliminary review of how AI is being used to enhance democratic practices worldwide, focusing on several themes including: accountability and transparency, elections, environmental democracy, inclusion, openness and participation, and women’s political leadership. The paper also highlights potential risks and areas of development in the future. Finally, the paper shares five recommendations for WFD and democracy support organisations to consider advancing their ‘digital democracy’ agenda. This policy paper also offers additional information regarding AI classification and other resources for identifying good practice and innovative solutions. Its findings may be relevant to WFD staff members, international development practitioners, civil society organisations, and persons interested in using emerging technologies within governmental settings…(More)”.

China’s biggest AI model is challenging American dominance

Curated on Posted on by Stefaan Verhulst

Article by Sam Eifling: “So far, the AI boom has been dominated by U.S. companies like OpenAI, Google, and Meta. In recent months, though, a new name has been popping up on benchmarking lists: Alibaba’s Qwen. Over the past few months, variants of Qwen have been topping the leaderboards of sites that measure an AI model’s performance.

“Qwen 72B is the king, and Chinese models are dominating,” Hugging Face CEO Clem Delangue wrote in June, after a Qwen-based model first rose to the top of his company’s Open LLM leaderboard.

It’s a surprising turnaround for the Chinese AI industry, which many thought was doomed by semiconductor restrictions and limitations on computing power. Qwen’s success is showing that China can compete with the world’s best AI models — raising serious questions about how long U.S. companies will continue to dominate the field. And by focusing on capabilities like language support, Qwen is breaking new ground on what an AI model can do — and who it can be built for.

Those capabilities have come as a surprise to many developers, even those working on Qwen itself. AI developer David Ng used Qwen to build the model that topped the Open LLM leaderboard. He’s built models using Meta and Google’s technology also but says Alibaba’s gave him the best results. “For some reason, it works best on the Chinese models,” he told Rest of World. “I don’t know why.”..(More)”